[avahi] Help wanted: review and prioritize pull requests
Petr Menšík
pemensik at redhat.com
Fri Nov 25 21:54:46 UTC 2022
Hello dear contributors,
because I have obtained commit rights to the avahi repository, I were
able to mark pull requests with various labels. I have spent couple
hours yesterday looking through the backlog. I think we should focus
first on bugs. I have marked some with important label [1], which I
think should receive higher priority. I have merged just translations. I
found multiple pull requests fixing just typo in comments or data files
and marked them with documentation label. They should be safe to merge
too, but I have left them just marked for now.
I would like to all others new maintainers to try to find time and
review those pull request. If you take a look at them, please use 'Files
changed' tab of a pull request and make a review. If you think that is
safe to merge, please approve that explicitly by using Review changes
button. I have found many changes just simple and safe fixes. But would
like other's opinion if possible. I have not approved my own pull
requests, I would like someone else to do that. Ideally every change
should be agreed on at least by two people. Let's test whether that can
work.
Some are more complex and I admit I lack detailed knowledge of mdns
protocol. Because there are no visible unit tests or regression testing,
I think a caution is required. I admit I use just quite a limited
features of mdns, mostly just addresses translations. It might be a good
idea to put together at least Markdown document with hints for testing.
I have noticed some test programs in avahi-core folder, but not any
description for its user. Slow way towards units test and make test
target would be great. But first things first.
If you disagree with my label assignments, please add comment(s) to the
appropriate PR. Thanks!
Regards,
Petr
1.
https://github.com/lathiat/avahi/pulls?q=is%3Apr+is%3Aopen+label%3Aimportant
--
Petr Menšík
Software Engineer, RHEL
Red Hat, https://www.redhat.com/
PGP: DFCF908DB7C87E8E529925BC4931CA5B6C9FC5CB
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